Tag: explainable AI
MLOps Startup Diveplane Raises $25M Series A
Diveplane, an MLOps startup based in Raleigh, N.C., has announced it raised $25 million in Series A funding. The company produces a suite of enterprise AI products that it says are designed around the principles of pr Read more…
AWS Adds Explainability to SageMaker
Amazon Web Services is adding an AI explainability reporting feature to its SageMaker machine learning model builder aimed at improving model accuracy. SageMaker Autopilot now generates a model explainability report Read more…
Restoring Supply Chains, Reducing Waste Via Explainable AI
The problem is wasteful supply chains clogged with excess inventory and defective parts. The goal is creating “perfect flow” for manufacturers and retailers to reduce waste running into the hundreds-of-billions dolla Read more…
NIST Launches Colloquy on Explainable AI
Among the best ways to create stable technologies are standards and specifications that provide a template for building trust while often seeding new technological ecosystems. That’s especially true for AI, where lack Read more…
Altair Shows Off Converged Analytics Lineup
If you’re in the market for analytics or machine learning software, you may want to keep your eyes on Altair Engineering. Best known for its product simulation and computer aided engineering software, Altair has quietl Read more…
Brief Perspective on Key Terms and Ideas in Responsible AI
Sponsored Content by H2O.ai
Introduction As fields like explainable AI and ethical AI have continued to develop in academia and industry, we have seen a litany of new methodologies that can be applied to improve our ability to trust and understand Read more…
The Next Generation of AI: Explainable AI
For most businesses, decisions -- from creating marketing taglines to which merger or acquisition to approve -- are made solely by humans using instinct, expertise, and understanding built through years of experience. Ho Read more…
Real Progress Being Made in Explaining AI
One of the biggest roadblocks that could prevent the widespread adoption of AI is explaining how it works. Deep neural networks, in particular, are extremely complex and resist clear description, which is a problem when Read more…
AIOps Startup with ‘Open’ Emphasis Raises Cash
Tech investors are betting that automated IT operations will be among the first significant enterprise applications for AI. Artificial intelligence for IT operations, or AIOps, and the application of machine learning Read more…
‘Social Contract’ Needed to Establish Trusted Data
With data emerging as the life blood of most industries, the emphasis has shifted from organizing and analyzing big data to finding ways to establish higher levels of trust in the torrent of data generated through custom Read more…
EU Ethics Rules Seek to Balance AI Risks, Benefits
European regulators continue to take the lead on a range of critical technology policy issues spanning data privacy and, now, “trustworthy” AI. On the heels of its sweeping General Data Protection Regulation, cons Read more…
DARPA Embraces ‘Common Sense’ Approach to AI
The Pentagon’s top research agency is focusing its considerable AI efforts on the interim stage of machine intelligence between “narrow” and “general” AI. The Defense Advanced Research Projects Agency (DARPA Read more…
Bright Skies, Black Boxes, and AI
Deep learning is popular today because it often works better than other machine learning approaches, particularly when large sets of training data are available. However, this form of AI doesn't always work well. And in Read more…
Opening Up Black Boxes with Explainable AI
One of the biggest challenges with deep learning is explaining to customers and regulators how the models get their answers. In many cases, we simply don't know how the models generated their answers, even if we're very Read more…
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